Method to obtain consistent image quality measurements from different image input devices

ABSTRACT

An image quality analysis system is provided for image output devices, such as printers and copiers, that overcomes problems with differences in analysis results caused by use of different image input devices. This is achieved by computing a differential transfer function that makes subsequent analysis device independent. Moreover, the analysis is performed on an image that has been blurred to also reflect absolute image quality metrics as seen by a human observer. By determining the resolving characteristics of the input scanner, the scanned image can be processed, with little or no artifacts, to resemble the image as perceived by a human observer, while at the same time eliminating differences that would arise when using a scanner having a different spatial resolving power.

BACKGROUND OF THE INVENTION

1. Field of Invention

This invention relates to an image quality analysis system that obtainsconsistent image quality measurements regardless of the particular imageinput device used.

2. Description of Related Art

It is well known that customer satisfaction can be improved andmaintenance costs reduced if problems with copiers and printers can befixed before they become serious enough to warrant a service call by thecustomer. While current technology exists to enable printers and copiersto call for service automatically when sensors detect certain operatingparameters outside of permissible ranges, there is not a verycomprehensive manner of detecting incipient system failure orautomatically diagnosing when problems with image quality reach a levelwhere human observers perceive a reduction in quality. This is causednot only by the large number of operating parameters that would need tobe tracked, but also because these parameters are strongly coupled toone another. That is, a given parameter at a certain value may or maynot be a problem depending on the values of other parameters. Whileexisting systems provide some level of image quality analysis, thesesystems have been found less than satisfactory as image qualitydetermination is machine dependent and may be inconsistent withperceptions of image quality as judged by human users.

SUMMARY OF THE INVENTION

Systems which can perform image analysis on printed test samples can beused in a variety of ways to provide solutions and value to users ofdigital printers and copiers, for example as the analysis engine forautomatic or remote diagnosis of print quality problems, or formonitoring quality as part of a print quality assurance system.

The system would typically use an input scanner, either stand-alone orpart of a multi-function printer/scanner/copier, to scan the printedtest sample, and then perform a series of analyses on the scanned image.Alternatively, a CCD camera could be used in place of the scanner. It isimportant to have consistent behavior of such systems, when used withdifferent input scanners. That is, the results of the analysis from oneinput scanner should be essentially identical to results from otherinput scanners. Only if this is the case, can the IQ measurements fromone such system be compared with other systems. In the case where thesystem is used by the printer/copier user, for example for IQ assurancepurposes, it is imperative that the results be consistent in order tocompare with industry standard measurements.

However, the input scanner is likely to be part of a multi-functionprinter/scanner/copier, and each system would therefore use a scannerwith different characteristics, especially in terms of spatial resolvingpower.

This invention overcomes problems with differences in analysis resultscaused by use of different image input devices by providing acomputational process that allows absolute image quality measurements tobe performed consistently from scans of print samples, largelyindependent of the resolving power of the scanner. Absolute imagequality metrics reflect quality as seen by a human observer. Bydetermining the resolving characteristics of the input scanner, thescanned image can be processed, with little or no artifacts, to resemblethe image as perceived by a human observer, while at the same timeeliminating differences that would arise when using a scanner having adifferent spatial resolving power, provided that the resolving power ofeach scanner is sufficiently greater than the resolving power of thehuman visual system.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be described with reference to the followingillustrative drawings, wherein like numerals refer to like elements andwherein:

FIG. 1 shows a typical digital copier machine having a user interfacesuitable for use with the invention;

FIG. 2 is a schematic diagram of a digital copier having a userinterface for communicating with a remote diagnostic computer;

FIG. 3 is a flow chart showing an image analysis method according to theinvention;

FIG. 4 is an alternative image output device and image analysis systemaccording to the invention;

FIG. 5 is a flow chart showing a more detailed image analysis methodaccording to the invention.

FIG. 6 shows examples of a human visual transfer function (VTF), as wellas several MTF for different scanners; and

FIG. 7 shows applying a simple processing according to the invention toimages scanned with two different devices.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

An exemplary device to which automatic image quality analysis is to beperformed will be described with reference to FIGS. 1-3. FIG. 1 shows animage output device, in particular a digital copier machine 10,comprising a plurality of programmable components and subsystems whichcooperate to carry out copying or printing jobs programmed through atouch dialog screen 42 of a user interface (UI) 11. Internal operatingsystems of the digital copier 10 are disclosed in U.S. Pat. Nos.5,038,319, 5,057,866, and 5,365,310, owned by the assignee of thepresent invention, the disclosures of which are incorporated herein byreference in their entirety. As such, no further detailed descriptionthereof is necessary. Digital copier 10, however, is merelyrepresentative of a preferred printing system to which the image qualitydetermination is made. It should be understood that a loosely coupledprinting or reproducing system is also applicable for use with theinvention described herein, such as a printer or facsimile device.Moreover, while there may be benefits to use of the image qualityanalysis on a reproduction system, such as a digital copier having anintegral scanner component, the invention also is applicable to aprinter used in conjunction with a stand-alone scanner, such as aflatbed type scanner.

Referring to FIG. 2, operation of the various components of exemplarydigital copier 10 is regulated by a control system which uses operatingsoftware stored in memory in the system controller 16 to operate thevarious machine components in an integrated fashion to produce copiesand prints. The control system includes a plurality of printed wiringboards (PWBs), there being a user interface module (UIM) core PWB 18, ascanner/imaging core PWB 20, an input station core PWB 22, a paperhandling core PWB 24 and an output station core PWB 26, together withvarious input/output (I/O) PWBs 28. A shared line (SL) 30 couples thecore PWBs 18, 20, 22, 24 and 26 with each other and with the electronicdata node core 32, while local buses 34 serve to couple the PWBs to therespective cores and to stepper and servo PWBs. Programming andoperating control over digital copier 10 is accomplished through touchdialog screen 42 of UI 11. The operating software includes applicationsoftware for implementing and coordinating operation of systemcomponents.

Floppy disk port 38 provides program loading access to UIM core PWB 18for the purpose of entering changes to the operating software, loadingspecific programs, such as diagnostic programs, and retrieving storeddata, such as machine history data and fault data, using floppy disks.Hard disk 36 is used as a non-volatile memory (NVM) to store programs,machine physical data and specific machine identity information. One ofthe programs hard disk 36 may store is image quality analysis softwarethat forms an image quality analysis module 70 used by the invention.Module 70 may also reside on a floppy disk used in floppy disk port 38.

UIM core PWB 18 communicates with video engine 40 for driving a suitablevisual display 42, such as a CRT or flat screen of the user interface11. The UIM core 18 also has connected thereto a control panel I/Oprocessor 44 and a generic accessories interface I/O processor 46. Theinterface I/O processor 46 is in turn connected to a modem PWB 48. Themodem 48 provides communication between digital copier 10 and acommunications channel, such as a public switched telephone network 50to facilitate information transfer to and from a remote diagnosticcomputer 60, which may also include image quality analysis module 70 aswell as other diagnostic modules.

The information from the subsystem cores flows to and from the UIM corePWB 18, which embodies software control systems including a userinterface system manager and a user interface manager. The UI systemmanager includes a UI display manager subsystem for controlling thedisplay of messages on the display 42. A data manager subsystem providesdata management to the UI system manager.

In a first embodiment of the invention, image quality analysis isperformed by the process set forth in the flow chart of FIG. 3. Theprocess starts at step S300 and advances to step S310 where at least onespecific digital test pattern, which can either be in hardcopy originalform or a digital image stored in memory 36, is provided. Preferably,multiple different test patterns are used to analyze various componentsrelevant to a determination of image quality. Flow then proceeds to stepS320 where a corresponding hardcopy output of the test pattern isgenerated. This can be by outputting a printed hardcopy output fromoutput station 26 using the digital test pattern as an input when thetest pattern is stored in digital form, such as in hard disk 36 orfloppy disk 38. Alternatively, an accurate original hardcopy testpattern may be placed at scanner 20 and scanned into the digital copier10 to form a digital test pattern, which can be used as an input tooutput station 26 to form the hardcopy output. Then, flow advances tostep S330 where the hardcopy output is scanned by scanner 20 to form adigital raster image for analysis purposes.

After step S330, flow advances to step S340 where the digital image ispreferably acted on by pattern recognition software, which can belocated within hard disk 36 or floppy disk 38 and is associated withimage quality analysis module 70, to determine a precise location ofvarious test elements within the scanned digital raster image. Thissoftware uses a Hough or similar transform to automatically detectlocator marks on the image. A suitable pattern recognition system foruse with the invention can be found in U.S. Pat. No. 5,642,202 toWilliams et al., owned by the assignee of the present invention, thedisclosure of which is incorporated herein by reference in its entirety.Alternatively, or in conjunction therewith, the test pattern may includea script that signifies a particular test pattern. The copier machine 10may hardware/software to decipher the particular script embedded intothe test pattern. The memory of the copier 10 may be provided with afile corresponding to each possible script detailing the contents of thescript and associated test pattern, as well as detailing the particularimage quality analysis routine to be used to measure a particular partof overall image quality. A more detailed description of such a scriptedtest pattern can be found in co-pending U.S. Ser. No. 09/450,182 toRasmussen et al., filed concurrently herewith, entitled “Method to AllowAutomated Image Quality Analysis of Arbitrary Test Patterns”, thesubject matter of which is incorporated by reference herein in itsentirety.

After step S340, the process flows to step S350 where image qualityanalysis is performed on the test image using image quality analysismodule 70. From step S350, flow advances to step S360 where adetermination is made by the image quality analysis module 70 whetherthe image quality for this particular test image is acceptable. If itis, flow advances to step S380 where the process stops. However, if theimage quality is not acceptable, flow advances from step S360 to stepS370 where a call can be made to a diagnostic facility. This call may bean automatic service call made through modem 48 for scheduling an actualservice visit by a service technician to correct the noted problems.Alternatively, it may be a call to a more sophisticated diagnosticmodule 80 located locally or at the remote facility that can furtheranalyze the image quality problem along with values from various sensorsand settings on the copier 10. This would provide corrective feedback tothe digital copier 10, such as through modem 48 when module 80 isremotely located, allowing the digital copier 20 to adjust itself withinacceptable parameters.

Alternatively, the image quality analysis module 70 may be remote fromimage output device 10. An example of which is illustrated in FIG. 4where image output devices are in the form of printers 10A, 10B whichare associated with a personal computer 60 through appropriate datacables. A flat bed scanner 20 is also associated with personal computer60 and image quality analysis module 70 is in the form of softwareprovided in personal computer 60. This embodiment operates as theprevious embodiment in that the printers 10A, 10B (which ever is beingtested) are given a test pattern to generate a hardcopy output from.This hardcopy output is then placed in scanner 20 to generate thedigital test image. This digital test pattern is then analyzed todetermine image quality of the printer. In the case where the imagequality analysis system is used not for machine diagnosis, but forexample for quality assurance, the results from step S350 would beprovided to the user of the system.

While shown in FIG. 4 to be loosely associated, the invention can alsobe practiced with completely discrete components, such as a separateprinter, scanner and computer or other source for containing imagequality analysis module 70. In this case, the hardcopy output from theprinter can be provided to a non-associated scanner for scanning. Then,the digital test image from the scanner can be stored or converted ontoa portable recording medium, such as a floppy disk and provided to anon-associated computer having the image quality analysis module.

The test pattern used can be one of several test patterns designed toprovide evaluation of one or more parameters relevant to image qualityanalysis of the output of the printing system, such as colorregistration, motion quality, micro and macro uniformity, colorcorrection, and font quality. This overall analysis is typicallyperformed using human visual perception models so that only thosedifferences that would be perceived by a human observer are determined.That is, rather than having the analysis merely compare a scanned imageto an original or to determine some level of variation or deviation froma given norm that may or may not rise to the level of a perceived imagequality issue when viewed by a human observer, the image qualityanalysis utilizes models of human visual perception. At a simple level,this can be achieved by passing the image through a band-pass filterknown to be similar in resolution to that achieved by a human visionsystem. More sophisticated modeling can also be used.

This particular invention relates specifically to providing consistentimage quality analysis of an image output device, such as a printer orcopier, regardless of the analysis equipment used. For a more detaileddescription of the overall image quality analysis system, see co-pendingU.S. Ser. No. 09/450,185 to Rasmussen et al., filed concurrentlyherewith, entitled “Virtual Tech Rep By Remote Image Quality Analysis”,the disclosure of which is incorporated herein by reference in itsentirety.

The ability of a scanner to resolve fine details in an image can becharacterized in terms of its sensitivity at different spatialfrequencies. This is usually referred to as the scanner's MTF(modulation transfer function).

For many applications it is necessary that image quality (IQ) metricsdirectly reflect quality as seen by a human observer. The human visualsystem (HVS), operating at normal viewing distances of 30 cm or more,typically has worse resolving power than image input devices such asflatbed scanners. Therefore, analysis of scanned images can falselyidentify print quality problems. Standard image quality metrics forgraininess, for example, take into account the sensitivity of the HVS atdifferent spatial frequencies. The sensitivity of the HVS at differentspatial frequencies is expressed through a so-called Visual TransferFunction (VTF), which is the human equivalent of the MTF of a scanner.

The ratio between the human VTF and the scanner MTF expresses, at eachspatial frequency, the extent to which the human visual system is lesssensitive than the scanner. We call this the differential transferfunction (DTF).

Image quality metric that quantify quality as perceived by a humanobserver, typically start with a scan of a printed test sample, and thenutilize a sequence of image processing steps, one or more of whichcorrespond to human visual processing as described by human visualmodels. For an example of such processing see co-pending U.S. Ser. No.09/450,180 to Rasmussen et al., filed concurrently herewith, entitled“Image Processing Algorithm For Characterization of Uniformity ofPrinted Images”, the disclosure of which is incorporated herein byreference in its entirety. Since the scanned image has already beendegraded (blurred) to some extent by the scanner, the image processingsteps corresponding to human visual perception, should utilize the DTF,rather than the VTF, in order to further transform the image to thepoint where it resembles what is perceived by the HVS.

Finally, various image analysis techniques can be applied to calculatespecific image quality measures, such as graininess and line darkness,from the transformed image that is independent from the individualscanner used to obtain the digital image. For an example of suchprocessing see co-pending U.S. Ser. No. 09/450,180 to Rasmussen et al.,filed concurrently herewith. See also co-pending U.S. Ser. No.09/450,177 to Rasmussen et al., filed concurrently herewith, entitled“Outline Font For Analytical Assessment of Printed Quality Text”, thedisclosure of which is incorporated herein in its entirety, relating toimage quality analysis of text.

An exemplary method for performing consistent image quality analysisaccording to the invention will be described with reference to FIG. 5.Before this process can start, the MTF of the specific scanner must havebeen determined. This needs be done only once for the given scanner, andin the case where the scanner is part of the multifunction device thatis being measured, the MTF of the scanner can be pre-determined by themanufacturer, and the results incorporated as a data file with the imagequality analysis software. Alternatively, a special, characterizedhardcopy test pattern, which is suitable for determination of scannerMTF, can be provided with the image quality analysis system, and one ofthe functions of the image quality analysis system can be to determinethe MTF of the particular scanner used, based on a scan of this hardcopytest pattern. The resulting scanner MTF data can then be stored in adata file for subsequent use by the image quality analysis system withthe specific scanner.

The process starts at step S500 and flow advances to step S510 where atleast one specific test pattern, which can either be in hardcopyoriginal form or a digital image stored in memory 36, is provided.Preferably, multiple different test patterns are used to analyze variouscomponents relevant to a determination of image quality. Flow thenproceeds to step S520 where a corresponding hardcopy output of the testpattern is generated. This can be by outputting a printed hardcopyoutput from output station 26 using the digital test pattern as an inputwhen the test pattern is stored in digital form, such as in hard disk 36or floppy disk 38. Then, flow advances to step S530 where the hardcopyoutput is scanned by scanner 20 to form a digital raster image foranalysis purposes. Each scanner has its own sensitivity and spatialresolution. After step S530, flow advances to step S540 where aparticular test image is detected. Then, flow advances to step S550where the pre-determined modulation transfer function (MTF) of theparticular scanner being used is obtained. This transfer function helpsto provide analysis that is device independent. It is also important forthe subsequent image quality analysis to reflect characteristics ofimage quality that are perceivable by human viewers. Accordingly, atransform according to human visual perception is also applied to theimage. Several human vision models are known from the literature, andall involve steps corresponding to application of a Visual TransferFunction (VTF) that blurs the image to some extent. From step S550, flowadvances to step S560 where by dividing the VTF by the MTF, adifferential transfer function (DTF) can be derived that reflects boththe particular characteristics of the human visual system and theparticular characteristics and resolving power of the scanner to providea device independent compensation value. From step S560, flow advancesto step S570 where the compensation function DTF is applied to thedigital image from step S530 to achieve an image that corresponds tothat perceived by a human viewer. Such an image is, as described above,largely device independent such that consistent comparisons can be madeand generated regardless of the particular scanner used. From step S570,flow advances to step S575 where image quality analysis is performed onthe compensated image.

At step S580, if the results of the image quality analysis indicate thata problem with image quality exists, flow may advance to step S590 wherea service call can be made to a service facility. If no problem exists,flow advances from step S580 to step S595 where the process stops.

The invention is useful in providing consistent image qualitymeasurements regardless of the particular image input device used andits particular resolving powers. For example, as shown in FIG. 6, threedifferent scanners are shown, each having differing MTFs (labeled MTF1,MTF2 and MTF3). Also shown is a human VTF. Even though the MTFs varygreatly from scanner to scanner, by using the inventive methods, aconsistent image quality analysis can be performed regardless of whichis used.

FIG. 7 shows a simple processing according to the invention applied toimages scanned from two different devices. Scanner SM-4000 and scannerUMAX were both used to scan a same printed halftone sample. The RMS ofthe pixel value deviation from the image average can be taken as asimple measure of uniformity, with a lower average being better. Whenthis was applied directly to the scanned images, as in (A) and (B), theRMS values were 26 and 15, respectively. The large difference is causedby the significantly better resolving power of the SM-4000 device.However, when a filter that represents the residual between the humanVTF and the device MTF is applied before RMS is calculated, as in (C)and (D), the agreement between the measurements using the two devicesbecomes excellent (4.0 versus 4.1).

Alternatively, two other methods could be used to avoid measurementsthat are affected by the resolving power of the instrument used toacquire the image data. However, neither of these alternatives arepractical for one or more reasons. The first can be used when thescanning equipment includes high resolution scanning microdensitometersand CCD cameras. As these scanners have very high resolving powers(resolution), their MTF can be neglected for this type of application.Thus, DTF becomes equal to the VTF, and the IQ analysis module cansimply use the VTF to obtain measurements that correlate with humanvisual perception. However, such instruments are very expensive anddifficult to operate. As such, these types of scanners will nottypically be used for routine image quality analysis outside dedicatedimage quality labs. While these instruments could be used in astand-alone environment, such as that shown in FIG. 2, they would not befeasible for self-diagnosing multipurpose devices, such as copiers andfacsimile machines as such scanners are cost-prohibited for suchcommercial products. As such, this alternative method is primarilylimited in application.

The second alternative method may be useful when image scanning isperformed by scanners with significant degradation caused by theirparticular MTF (i.e., not case 1 above). Many scanners can be“corrected” based on knowledge of the MTF. For example, typical flatbedscanner systems include options to sharpen the image in order tocompensate for the loss of sharpness caused by the limitations in theMTF. However, such algorithms which compensate for the MTF and try toreestablish the image as it would have been recorded by a perfectscanning device are prone to generate artifacts in the image. Theseartifacts may significantly impact the results of the IQ analysis. Assuch, this alternative also has its disadvantages and is not suitablefor the purposes discussed here.

With the present invention, relatively inexpensive image scanningdevices can be used for the image quality analysis, despite theirlimitations and differences in terms of MTF. In particular, scannersthat are part of a multi-function printer/scanner/copier can be used,and yet provide consistent IQ measurements. The image processingrequired to apply the DTF can be performed without introduction ofartifact, since it does not attempt to directly correct for the MTF ofthe scanner, but essentially only blurs the image further, to the pointwhere it resembles the visually perceived image.

Several straight-forward extensions and/or modifications of theinvention are possible, including:

1. In addition to the correction for spatial resolving power of thedevices, a color calibration can be applied. This is further describedin co-pending U.S. Ser. No. 09/450,185 to Rasmussen et al., filedconcurrently herewith, entitled “Virtual Tech Rep By Remote ImageQuality Analysis”.

2. The invention has been described mainly in terms of frequency-domaincharacterization of scanner and human visual perception, that is, interm of MTF and VTF which provide sensitivity at different spatialfrequencies. However, the actual processing of images is often betterdone using real-space convolution kernels, which correspond to thefrequency-space MTF or VTF. Therefore, the invention could equivalentlyhave been described in terms of convolution kernels. The critical pointis that, when the image is processed (whether in frequency—orreal-space) to represent the humanly perceived image, the scannerresolving power characteristics are factored out.

What is claimed is:
 1. An image quality analysis system for an imageoutput device that is input device independent, comprising: a testpattern pertinent to image quality determination; a scanner that scans ahardcopy test image, which has been generated by the output device basedon the test pattern, to form a digital raster image, the scanner havinga predetermined modulated transfer function (MTF); means for blurringthe digital raster image by a differential transfer function (DTF)corresponding to the modulation transfer function (MTF) divided by thevisual transfer function (VTF) corresponding to a human visual system toform a blurred image; and an image quality analysis module that receivesthe blurred image, distinguishes one or more test targets from theblurred image, and performs image quality analysis on the test targetsto obtain results quantifying image quality, wherein the results of theimage quality analysis are scanner independent and the blurred imagefrom which the image analysis was conducted corresponds to an imageperceived by a human viewer when viewing the hardcopy test image.
 2. Theimage quality analysis system of claim 1, wherein the image qualityanalysis module resides locally at a site of the image output device. 3.The image quality analysis system of claim 2, wherein the image outputdevice is a copier that contains the scanner.
 4. The image qualityanalysis system of claim 1, wherein the scanner and the image qualityanalysis module reside remote from the image output device.
 5. The imagequality analysis system of claim 1, wherein the test pattern is storedin memory at the image output device.
 6. The image quality analysissystem of claim 1, wherein the image output device is a copier having aninput scanner section serving as the scanner and an output printersection, and the test pattern is in the form of a hardcopy printout thatis subsequently scanned into the input scanner section and output as thehardcopy test image.
 7. The image quality analysis system of claim 6,further comprising a communication module that connects the imagequality analysis module to a remote facility.
 8. The image qualityanalysis system of claim 7, wherein the results of the image qualityanalysis are forwarded to the remote facility through the communicationmodule.
 9. The image quality analysis system of claim 8, wherein theremote facility includes a diagnostic module that returns informationpertinent to correcting any undesirable image quality test results. 10.A method of performing image quality analysis on an image output devicehaving an output station that generates a hardcopy image from a digitalimage, the method comprising: generating a hardcopy test image from theimage output device based on a predetermined test pattern pertinent toimage quality determination; scanning the hardcopy test image using ascanner to form a digital raster image; determining a ModulationTransfer Function (MTF) for the scanner at different spatialfrequencies; determining a Visual Transfer Function (VTF) to take intoaccount the sensitivity of a human visual system (HVS); calculating aDifferential Transfer Function (DTF) at each spatial frequencyreflecting the difference between MTF and VTF; transforming the scanneddigital test image according to the DTF to degrade or blur the image tosome extent from that achieved by the scanner such that this blurredimage represents the image perceived by the human vision system (HVS);and performing the image quality analysis based on the blurred image.11. The method of claim 10, wherein the results of the image qualityanalysis are scanner independent and the blurred image from which theimage analysis was conducted corresponds to an image perceived by ahuman viewer when viewing the hardcopy test image.
 12. The method ofclaim 10, further comprising a step of sending a communication to aservice facility indicating the results of the image quality analysis.13. The method of claim 10, wherein the communication is a service callif the image quality results are less than desirable.
 14. The method ofclaim 10, further comprising the steps of analyzing the results alongwith predetermined image output device operating parameters andcommunicating information to the image output device relevant tocorrecting the undesirable image quality.
 15. The method of claim 10,wherein the image output device is a copier that contains the scanner.16. The method of claim 10, wherein the method is automaticallyinitiated by the copier at a predetermined time.
 17. The method of claim10, wherein the steps of scanning and analyzing are performed remotefrom the image output device.
 18. A multi-function output device,including a scanner, and an associated data file provided on a storagemedium that defines pre-determined data, usable to transform imagesscanned by the device into device-independent images that represent howthe scanned sample would be perceived by a human observer, the datadefining a single transform representing a Differential TransferFunction (DTF) that reflects a difference between a Modulation TransferFunction (MTF) that takes into account the scanner resolving power ofthe scanner and a Visual Transfer Function (VTF) that takes into accountthe sensitivity of a Human Visual System (HVS).
 19. The multi-functionoutput device of claim 18, where the data is in the form of space-domainconvolution kernels.